docstr: Args:
      sentence: string, the input sentence
      is_token: if is_token == True, senetence becomes an array of token
  Return:
      [{name: xx, pos: [start, end]}], a list of named entities
docstr_tok: ["Args",":","sentence",":","string",",","the","input","sentence","is_token",":","if","is_token","==","True",",","senetence","becomes","an","array","of","token","Return",":","[","{","name",":","xx",",","pos",":","[","start",",","end","]","}","]",",","a","list","of","named","entities"]
code: def ner(self, sentence, is_token=False):
      """
      Args:
          sentence: string, the input sentence
          is_token: if is_token == True, senetence becomes an array of token
      Return:
          [{name: xx, pos: [start, end]}], a list of named entities
      """
      raise NotImplementedError
  
file_path: OpenNRE/opennre/model/base_model.py
imports: import torch
  from torch import nn
  import json
label_desc: Use image node_id 2 for calling the NER obj's underlying member method code with example usage: obj.ner(sentence, is_token) without return types